most citedHuman-in-the-loop: Provably Efficient Preference-based Reinforcement Learning with General Function Approximation

2 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2022★ 2 cited

Human-in-the-loop: Provably Efficient Preference-based Reinforcement Learning with General Function Approximation

Xiaoyu Chen, Han Zhong, Zhuoran Yang +2

We study human-in-the-loop reinforcement learning (RL) with trajectory preferences, where instead of receiving a numeric reward at each step, the agent only receives preferences ov…

cs.LG2021

Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs

Han Zhong, Jiayi Huang, Lin F. Yang +1

Despite a large amount of effort in dealing with heavy-tailed error in machine learning, little is known when moments of the error can become non-existential: the random noise …